Algorithms for collision-free navigation of mobile robots in complex cluttered environments: A survey

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Algorithms for collision-free navigation of mobile robots in complex cluttered environments: A survey. / Hoy, M.; Matveev, A.S.; Savkin, A.V.

In: Robotica, No. 3, 2015, p. 463-497.

Research output: Contribution to journal › Article

BibTeX

@article{ae7f622391654b889ef94d9fc5163e16,

title = "Algorithms for collision-free navigation of mobile robots in complex cluttered environments: A survey",

abstract = "{\textcopyright} 2014 Cambridge University Press.We review a range of techniques related to navigation of unmanned vehicles through unknown environments with obstacles, especially those that rigorously ensure collision avoidance (given certain assumptions about the system). This topic continues to be an active area of research, and we highlight some directions in which available approaches may be improved. The paper discusses models of the sensors and vehicle kinematics, assumptions about the environment, and performance criteria. Methods applicable to stationary obstacles, moving obstacles and multiple vehicles scenarios are all reviewed. In preference to global approaches based on full knowledge of the environment, particular attention is given to reactive methods based on local sensory data, with a special focus on recently proposed navigation laws based on model predictive and sliding mode control.",

author = "M. Hoy and A.S. Matveev and A.V. Savkin",

year = "2015",

doi = "10.1017/S0263574714000289",

language = "English",

pages = "463--497",

journal = "Robotica",

issn = "0263-5747",

publisher = "Cambridge University Press",

number = "3",

}

RIS

TY - JOUR

T1 - Algorithms for collision-free navigation of mobile robots in complex cluttered environments: A survey

AU - Hoy, M.

AU - Matveev, A.S.

AU - Savkin, A.V.

PY - 2015

Y1 - 2015

N2 - © 2014 Cambridge University Press.We review a range of techniques related to navigation of unmanned vehicles through unknown environments with obstacles, especially those that rigorously ensure collision avoidance (given certain assumptions about the system). This topic continues to be an active area of research, and we highlight some directions in which available approaches may be improved. The paper discusses models of the sensors and vehicle kinematics, assumptions about the environment, and performance criteria. Methods applicable to stationary obstacles, moving obstacles and multiple vehicles scenarios are all reviewed. In preference to global approaches based on full knowledge of the environment, particular attention is given to reactive methods based on local sensory data, with a special focus on recently proposed navigation laws based on model predictive and sliding mode control.

AB - © 2014 Cambridge University Press.We review a range of techniques related to navigation of unmanned vehicles through unknown environments with obstacles, especially those that rigorously ensure collision avoidance (given certain assumptions about the system). This topic continues to be an active area of research, and we highlight some directions in which available approaches may be improved. The paper discusses models of the sensors and vehicle kinematics, assumptions about the environment, and performance criteria. Methods applicable to stationary obstacles, moving obstacles and multiple vehicles scenarios are all reviewed. In preference to global approaches based on full knowledge of the environment, particular attention is given to reactive methods based on local sensory data, with a special focus on recently proposed navigation laws based on model predictive and sliding mode control.

U2 - 10.1017/S0263574714000289

DO - 10.1017/S0263574714000289

M3 - Article

SP - 463

EP - 497

JO - Robotica

JF - Robotica

SN - 0263-5747

IS - 3

ER -

ID: 4009953